scholarly journals The effect of age at first calving on the milking performance of primiparous Jersey cows

2021 ◽  
Vol 17 (1) ◽  
pp. 1-10
Author(s):  
Jarosław Pytlewski ◽  
Ireneusz Ryszard Antkowiak
Keyword(s):  
Milk Yield ◽  
Age At First Calving ◽  
Exact Test ◽  
Lactation Curve ◽  
Younger Age ◽  
Daily Milk Yield ◽  
Linear Graphs ◽  
Jersey Cows ◽  
Effect Of Age ◽  
Daily Milk

<b>The aim of this study was to determine the effect of age at first calving on the milking performance of primiparous Jersey cows (261 cows). Analyses were conducted on 2461 test day milking samples from 17.09.2007 to 26.07.2016. The primiparous cows were divided into four groups according to their age at first calving (≤ 24, > 24–26, > 26–28, > 28 months), and their daily milk yields were compared. Fourfold contingency tables were prepared to investigate the distribution of the population of cows calving at different ages and the peak daily milk yield. The significance of the association between factors was estimated using Fisher's exact test. To illustrate the course of 305-day lactation in primiparous cows varying in age at first calving, linear graphs were plotted with linear trends for daily milk yields. Primiparous Jersey cows calving at the age of > 26–28 months of life had the highest daily milk yield. In terms of the contents of basic milk constituents in the first lactation, the most advantageous age at first calving was > 24–26 months of life. However, a younger age at first calving (≤ 24 months) was associated with a lower somatic cell count in milk as well as a more favourable lactation curve for daily milk yield. The results of the study may suggest that Jersey cows calving at an earlier age (up to 24 months) may have a longer productive life and thus better performance parameters.

scholarly journals Comparison of different lactation curve models in Holstein cows raised on a farm in the south-eastern Anatolia region

2008 ◽  
Vol 51 (4) ◽  
pp. 329-337
Author(s):  
Ö. Koçak ◽  
B. Ekiz
Keyword(s):  
Milk Yield ◽  
Goodness Of Fit ◽  
Mean Squared Error ◽  
Exponential Model ◽  
Eastern Anatolia ◽  
Mean Squared Errors ◽  
Squared Error ◽  
Lactation Curve ◽  
Daily Milk Yield ◽  
Daily Milk

Abstract. The objective of this study was to compare the goodness of fit of seven mathematical models (including the gamma function, the exponential model, the mixed log model, the inverse quadratic polynomial model and their various modifications) on daily milk yield records. The criteria used to compare models were mean R2, root mean squared errors (RMSE) and difference between actual and predicted lactation milk yields. The effect of lactation number on curve parameters was significant for models with three parameters. Third lactation cows had the highest intercept post-calving, greatest incline between calving and peak milk yield and greatest decline between peak milk yield and end of lactation. Latest peak production occurred in first lactation for all models, while third lactation cows had the earliest day of peak production. The R2 values ranged between 0.590 and 0.650 for first lactation, between 0.703 and 0.773 for second lactation and between 0.686 and 0.824 for third lactation, depending on the model fitted. The root mean squared error values of different models varied between 1.748 kg and 2.556 kg for first parity cows, between 2.133 kg and 3.284 kg for second parity cows and between 2.342 kg and 7.898 kg for third parity cows. Lactation milk yield deviations of Ali and Schaeffer, Wilmink and Guo and Swalve Models were close to zero for all lactations. Ali and Schaeffer Model had the highest R2 for all lactations and also yielded smallest RMSE and actual and predicted lactation milk yield differences. Wilmink and Guo and Swalve Models gave better fit than other three parameter models.

scholarly journals On designing the average lactation curve at the ascending phase

1962 ◽  
Vol 34 (1) ◽  
pp. 162-168
Author(s):  
Aarne Mäkelä
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Lactation Period ◽  
Lactation Curve ◽  
The Mean ◽  
The Individual ◽  
Daily Milk Yield ◽  
Daily Milk

Comparisons are made between different methods to find the peak production (maximum daily milk yield) and methods to design the average lactation curve at the ascending phase in dairy cows. It was noted that in order to determine the height and location of the maximal producing capacity of a cow in a known lactation period, it is preferable to choose the peak production as a mean of three subsequent best days. It was also noted that the usual methods for drawing the average lactation curves do not give a true picture of the height and location of the peak. The author suggests a method for determining the average lactation curve at the ascending phase by using the averages of both milk productions and times involved in reaching the peak and known fractions (e.g. 1/8, 1/4, 1/2, 3/4, and 5/4) of it. In this lactation curve the peak production is the mean of the peaks of individual cows, and the time involved in reaching it is the mean of the durations of the ascending phases of the individual cows.

scholarly journals Associations between milking technology, herd size and milk production parameters on commercial dairy cattle farms

2020 ◽  
Vol 70 (2) ◽  
pp. 103-111
Author(s):  
Dorottya Ivanyos ◽  
László Ózsvári ◽  
István Fodor ◽  
Csaba Németh ◽  
Attila Monostori
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Milk Yield ◽  
Linear Models ◽  
Herd Size ◽  
Exact Test ◽  
Production Parameters ◽  
Daily Milk Yield ◽  
Cattle Farms ◽  
Daily Milk

The aim of the study was to survey the milking technology and to analyse the associations between milking parlour type, herd size, and milk production parameters on dairy cattle farms. The milking technology was surveyed by using a questionnaire in 417 Hungarian dairy herds with 177,514 cows in 2017, and it was compared with their official farm milk production data. The surveyed farms were categorized according to their size (1-50, 51-300, 301-600, and &gt;600 cows) and to their milking parlour types (herringbone, parallel, carousel, and others). The relationships were analysed by multivariate linear models, one-way ANOVA, and Fisher’s exact test. Pairwise comparisons were performed by Tukey’s post hoc tests. The prevailing type of milking parlour was herringbone (71.0 %), but on larger farms the occurrence of parallel and carousel parlours increased (p&lt;0.001). The number of milking stalls per farm increased with herd size (p&lt;0.001). Farms with herringbone parlour had significantly smaller number of milking stalls than that of parallel (p=0.022) and carousel (p&lt;0.001) parlours, and the cows were mostly milked two times, while in carousel milking parlours mostly three times a day. As the herd size increased, so did daily milk yield (p&lt;0.001) and daily milk production per cow (p&lt;0.001). Herd size was associated with somatic cell count (p&lt;0.001). The type of milking parlour showed significant association with daily milk yield (p=0.039) and dairy units with herringbone milking system had the lowest milk quality. Our findings show that herd size has greater impact on milk production parameters than milking technologies.

scholarly journals Test-day model of daily milk yield prediction across stages of lactation in Egyptian buffaloes

2003 ◽  
Vol 46 (1) ◽  
pp. 35-45 ◽  
Author(s):  
A. A. Amin
Keyword(s):  
Milk Yield ◽  
Prediction Equation ◽  
Total Variance ◽  
Yield Prediction ◽  
Prediction Equations ◽  
Data Set ◽  
Age At First Calving ◽  
Stage Of Lactation ◽  
Daily Milk Yield ◽  
Daily Milk

Abstract. farms in Ismailia region, which exist east of Cairo. Two data sets were considered for analysis of variance according to lactation length. The first data set is TDY of the short lactation (5–10 months: LPS). The 2nd data set is the TDY of the long lactation (LPL > 305 days). Daily milk yield prediction equations were investigated using multiple lactations, separate lactations, and three groups of age at first calving. Polynomial regression functions were fitted to study the effect of stage of lactation on variation in test-day milk yield observations (TDY). Results of the present study showed that the effect of herd (farm, season and year of calving) on variation of TDY were significant and accounted for 35.22% of the total variance for the data set of LPL. Variations in TDY due to the effect of either order of lactation or age at first calving groups were significant and accounted for 8.25% and 13.50%, respectively of the total variance. The overall least-square means of TDY were 5.5 and 7.8 Kg for LPS and LPL, respectively. The highest frequencies of similar TDY observations appeared in the early months across stage of lactation. The peak of the measured TDY obtained among the 4th and the 6th month of lactation of the pooled parity data set. Prediction equation of TDY across days of lactation (Days in Milk:DIM) using pooled parities was as the following: Y = 3.4103 +.0466X − .0004X2 + .00001X3 − 1.03E-8X4 Prediction equation of TDY across months of lactation (Months in Milk:MIM) using pooled parity data set was as the following: Y = 1.9634 + 2.7927X − .8931X2 + .1602X3 − .0138X4. Prediction equations for TDY per parity and for each age at first calving group were computed.

scholarly journals Factors affecting milk yield and ewe’s lactation curves estimated with test-day models

2011 ◽  
Vol 51 (No. 11) ◽  
pp. 483-490 ◽  
Author(s):  
M. Oravcová ◽  
M. Margetín ◽  
D. Peškovičová ◽  
J. Daňo ◽  
M. Milerski ◽  
...  
Keyword(s):  
Linear Model ◽  
Litter Size ◽  
Milk Yield ◽  
Fixed Effects ◽  
General Linear Model ◽  
Yield Variability ◽  
Factors Affecting ◽  
Lactation Curve ◽  
Daily Milk Yield ◽  
Daily Milk

Test-day records of purebred Tsigai, Improved Valachian and Lacaune ewes were analysed with a general linear model in order to investigate the effects of flock-test day, lactation number, days in milk, litter size and month of lambing. In total, 121 576 (Tsigai), 247 902 (Improved Valachian) and 2 196 (Lacaune) test-day records gathered over the period 1995&ndash;2005 were included in the analyses. Average daily milk yields were 0.604 &plusmn; 0.279 kg (Tsigai), 0.595 &plusmn; 0.243 kg (Improved Valachian) and 1.053 &plusmn; 0.475 kg (Lacaune). The significant (P &lt; 0.05) or highly significant (P &lt; 0.01) effects of flock-test day, lactation number (except for Lacaune), days in milk, litter size (except for Lacaune) and month of lambing (either fixed effects or covariates) tested by Fisher&rsquo;s tests were shown. The model explained about 50% of daily milk yield variability, with coefficients of determination as follows: 0.479 for Improved Valachian; 0.487 for Tsigai; 0.537 for Lacaune. Differences in estimated least-squares means were tested using multiple-range Scheffe&rsquo;s tests. A lower daily milk yield was found for the first lactation, single litter and lactations starting in March in comparison with daily milk yield for the second and third lactations (except for Lacaune), multiple litter and lactations starting in January and February (except for Improved Valachian). Ali-Schaeffer regression adopted for sheep was used for the fitting of lactation curve according to breed. &nbsp;

scholarly journals Genetic and environmental parameters estimation for milk traits in Slovenian dairy sheep using random regression model

2013 ◽  
Vol 58 (No. 3) ◽  
pp. 125-135 ◽  
Author(s):  
A. Komprej ◽  
Š. Malovrh ◽  
G. Gorjanc ◽  
D. Kon ◽  
M. Kovač
Keyword(s):  
Regression Model ◽  
Protein Content ◽  
Milk Yield ◽  
Random Regression ◽  
Dairy Sheep ◽  
Milk Traits ◽  
Random Regression Model ◽  
Lactation Curve ◽  
Daily Milk Yield ◽  
Daily Milk

(Co)variance components for daily milk yield, fat, and protein content in Slovenian dairy sheep were estimated with random regression model. Test-day records were collected by the ICAR A4 method. Analysis was done for 38 983 test-day records of 3068 ewes in 36 flocks. Common flock environment, additive genetic effect, permanent environment effect over lactations, and permanent environment effect within lactation were included into the random part of the model and modelled with Legendre polynomials on the standardized time scale of days in lactation. Estimation of (co)variance components was done with REML. The eigenvalues of covariance functions for random regression coefficients were calculated to quantify the sufficient order of Legendre polynomial for the (co)variance component estimation of milk traits. The existing 13 to 24% of additive genetic variability for the individual lactation curve indicated that the use of random regression model is justified for selection on the level and shape of lactation curve in dairy sheep. Four eigenvalues sufficiently explained variability during lactation in all three milk traits. Heritability estimate for daily milk yield was the highest in mid lactation (0.17) and lower in the early (0.11) and late (0.08) lactation. In fat content, the heritability was increasing throughout lactation (0.08&ndash;0.13). Values in protein content varied from the beginning toward mid lactation (0.15&ndash;0.19), while they rapidly increased at the end of lactation (0.28). Common flock environment explained the highest percentage of phenotypic variability: 27&ndash;41% in daily milk yield, 31&ndash;41% in fat content, and 41&ndash;49% in protein content. Variance ratios for the two permanent environment effects were the highest in daily milk yield (0.10&ndash;0.27), and lower in fat (0.04&ndash;0.08) and protein (0.01&ndash;0.10) contents. Additive genetic correlations during the selected test-days were high between the adjacent ones and they tended to decrease at the extremes of the lactation trajectory.

scholarly journals  Lactation curves for milk yield, fat and protein content in Slovenian dairy sheep

2012 ◽  
Vol 57 (No. 5) ◽  
pp. 231-239 ◽  
Author(s):  
A. Komprej ◽  
G. Gorjanc ◽  
D. Kon ◽  
M. Kovač
Keyword(s):  
Animal Model ◽  
Protein Content ◽  
Litter Size ◽  
Milk Yield ◽  
Additive Genetic Effect ◽  
Dairy Sheep ◽  
Stage Of Lactation ◽  
Lactation Curve ◽  
Daily Milk Yield ◽  
Daily Milk

Lactation curves for daily milk yield, fat, and protein content in three dairy sheep breeds were estimated by the repeatability animal model using test-day records. A total of 38 983 records from 3068 ewes of Bovec, Improved Bovec, and Istrian Pramenka breeds, collected between the years 1994 and 2002, were analysed. The three-trait repeatability animal model included breed and lambing season as fixed. The stage of lactation within each breed was modelled by the modified Ali-Schaeffer&rsquo;s lactation curve. Parity and litter size were used as covariates in quadratic and linear regression, respectively. Common flock environment, additive genetic effect, permanent environment over lactations as well as within lactation were treated as random. The average daily milk yield was 1090 g in Bovec, 1010 g in Improved Bovec, and 731 g in Istrian Pramenka breeds. Overall means for fat and protein content were 6.59 and 5.53% for Bovec, 6.22 and 5.33% for Improved Bovec, and 7.20 and 5.63% for Istrian Pramenka. Breed, lambing season, stage of lactation, parity, and litter size significantly (P &lt; 0.001) affected all three observed milk traits, with the only exception of parity in fat and litter size in protein content. The shape of lactation curves for daily milk yield in Bovec and Improved Bovec breeds fitted well to the general lactation curve in dairy sheep. Daily milk yield was increasing in the first month of lactation and decreasing thereafter. In Istrian Pramenka, the shape of lactation curve was more or less atypical, with daily milk yield decreasing almost throughout the entire lactation. Lactation curves for fat and protein content were opposite to the lactation curves for daily milk yield in all three breeds. &nbsp;

scholarly journals Conditioning Factors of Linearized Wood’s Function Lactation Curve Shape Parameters, Milk Yield, Fat and Protein Content in Murciano-Granadina Primiparous Does

Animals ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 2115
Author(s):  
Juan Vicente Delgado Bermejo ◽  
Francisco Antonio Limón Pérez ◽  
Francisco Javier Navas González ◽  
Jose Manuel León Jurado ◽  
Javier Fernández Álvarez ◽  
...  
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Random Regression ◽  
Total Production ◽  
Curve Shape ◽  
Conditioning Factors ◽  
Lactation Length ◽  
Lactation Curve ◽  
Daily Milk Yield ◽  
Daily Milk

A total of 137,927 controls of 22,932 Murciano-Granadina first lactation goats (measured between 1996–2016) were evaluated to determine the influence of the number of kids, season, year and farm on total milk yield, daily milk yield, lactation length, total production of fat and protein and percentages of fat and protein. All factors analyzed had a significant effect on the variables studied, except for the influence of the number of kids on the percentages of fat and protein, where the variation was very small. Goats with two offspring produced nearly 15% more milk, fat and protein per lactation compared to goats with simple kids. Kiddings occurring in summer–autumn resulted in average milk, fat and protein yields nearly 14, 19 and 23% higher when compared to winter–spring kiddings. Lactation curves were evaluated to determine the effects of the number of kids and season, using the linearized version of the model of Wood in random regression analyses. Peak Yield increased by about 0.3 kg per additional offspring at kidding, but persistence was higher in goats with single offspring. The kidding season significantly influenced the lactation curve shape. Hence summer-kidding goats were more productive, and peak occurred earlier, while a higher persistence was observed in goats kidding during autumn.

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